Bubbles-Induced Porous Structure-Based Flexible Piezoresistive Sensors for Speech Recognition

Abstract

Flexible piezoresistive sensors with a porous structure that are used in the field of speech recognition are seldom characterized by both high sensitivity and ease of preparation. In this study, a piezoresistive sensor with a porous structure that is both highly sensitive and can be prepared by using a simple method is proposed for speech recognition. The preparation process utilizes the interaction of bubbles generated by ethanol evaporation and active agents with polydimethylsiloxane to produce a porous flexible substrate. This preparation process requires neither templates nor harsh experimental conditions such as a low temperature and a low pressure. Furthermore, the prepared piezoresistive sensor has excellent properties, such as a high sensitivity (27.6 kPa −1 ), a satisfactory response time (800 μs), and a good stability (10,000 cycles). When used for speech recognition, more than 1500 vocalizations and silent speech signals obtained from subjects saying numbers from "0" to "9" were collected by the sensor for training a convolutional neural network model. The average accuracy of the recognition reached 94.8%. The simple preparation process and the excellent performance of the prepared flexible piezoresistive sensor endow it with a wide application prospect in the field of speech recognition.

All-Textile Piezoelectric Nanogenerator Based on 3D Knitted Fabric Electrode for Wearable Applications

“…They can convert external mechanical actions into recognizable signals in real-time. Recently, they have attracted much attention. − Wearable flexible sensors with different sensing mechanisms have been developed, mainly including piezoresistive, capacitive, triboelectric, and piezoelectric flexible sensors. Piezoresistive sensors respond to external stimuli by changing resistance, and the performance of many piezoresistive sensors depends on the mechanical stability of the conductive network.…”